Concentric data visualization structures

ABSTRACT

A concentric data visualization structure for displaying a plurality of attributes specific to a dataset includes a percentage ring, a proportion ring and a count ring. The percentage ring indicates a percentage representative of an attribute of the dataset and comprises an arc having an arc length corresponding to the percentage. The proportion ring includes a plurality of wedges that make up a whole. Each wedge represents a percentage proportion of the whole and also represents an attribute of the dataset. The wedges, when displayed, fill the entirety of the proportion ring. The count ring indicates a count value representative of an attribute of the dataset. The count ring comprises a segmented circle where the number of the segments of the circle correspond to the count value.

TECHNICAL FIELD

The present disclosure is directed to graphical displays of data and,more particularly, to the creation and rendering of concentric datavisualization structures.

BACKGROUND

Data visualization is an important part of understanding and workingwith data. However, data visualization is difficult in the instance oflarge datasets with dozens or possibly even hundreds of dimensions. Asingle pie chart, bar graph or line chart, for example, are simply notsufficient to visualize and discover patterns, trends and correlationswithin a large dataset. Rather, there is a need for a data visualizationstructure that can incorporate a plurality of data dimensions in asingle diagram.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used to limit the scope of the claimed subject matter.

The present disclosure is directed to systems and methods for creatingand rendering concentric data visualization structures. The concentricdata visualization structures have the ability to represent virtuallyany number of features associated with small or large datasets. The datavisualization structures are created and rendered in the form of aconcentric ring diagram (however, concentric shapes other than a ringcan be used), wherein a plurality of concentric rings are used torepresent a plurality of data attributes associated with a dataset. Incertain examples, the dataset represents spending transactions between aretail guest and a retailer. Further, in certain examples, the spendingtransactions are those occurring at one or more physical sites of theretailer and/or one or more e-retail websites of the retailer. Thespending transactions are analyzed to determine one or more dataattributes; the determined data attributes are typically expressed inthe form of a numerical value. One of three ring-types is assigned toeach data attribute according to the type of data attribute. The threering-types include: a percentage ring, a proportion ring, and a countring. Display features of the rings are defined to assist indistinguishing one ring from another. Such display features can include,but are not limited to, a concentric display order, a display color, adisplay pattern, and an inner and outer diameter of the ring (e.g.,thickness). The determined data attributes, assigned rings and displayfeatures are used to generate instructions for constructing one or moreof the concentric ring diagrams. The one or more concentric ringdiagrams are then rendered as one or more visual images on one or moredisplay devices according to the instructions providing a compactvisualization of a plurality of data attributes. In certain embodiments,26 data attributes are visualized in a single concentric ring diagramwhile in other embodiments the 26 data attributes are spread among aplurality of concentric ring diagrams. A number of data attributesgreater or lesser than 26 data attributes in a single concentric ringdiagram are also possible.

An aspect of the present disclosure is directed to a method forvisualizing data of a dataset. The method includes receiving the datasetand determining a plurality of data attributes that represent thedataset. Each of the determined data attributes are represented by apercentage value, a proportion value of a whole value or a count value.The method further includes associating a ring-type with each determinedattribute according to the value with which the determined dataattribute is represented. A percentage ring-type is associated with thepercentage value, a proportion ring-type is associated with theproportion value of the whole value, and a count ring-type is associatedwith the count value. The percentage ring-type indicates the percentagevalue with an exposed arc length that corresponds to the percentagevalue. The proportion ring-type indicates the proportion value of thewhole value with a wedge-shape having a size corresponding to theproportion value. The count ring-type indicates the count value with asegmented ring; the number of segments in the ring corresponding to thecount value. The method further includes generating instructions forrendering a concentric visualization data structure that includes aleast one percentage ring-type, at least one proportion ring-type and atleast one count ring-type. The method also includes rendering theconcentric visualization data structure as an image of at least first,second and third concentric rings which correspond to the percentagering-type, the proportion ring-type and the count ring-type,respectively.

Another aspect of the present disclosure is directed to a concentricdata visualization structure for displaying a plurality of attributesspecific to a dataset. The concentric data visualization structureincludes a percentage ring, a proportion ring and a count ring. Thepercentage ring indicates a percentage representative of an attribute ofthe dataset and comprises an arc having an arc length corresponding tothe percentage. The proportion ring includes a plurality of wedges thatmake up a whole. Each wedge represents a percentage proportion of thewhole and also represents an attribute of the dataset. The wedges, whendisplayed, fill the entirety of the proportion ring. The count ringindicates a count value representative of an attribute of the dataset.The count ring comprises a segmented circle where the number of thesegments of the circle correspond to the count value.

Still another aspect of the present disclosure is directed to a systemfor visualizing data of a dataset. The system includes a display device,a memory device storing executable instructions and a processing devicein communication with the display device and the memory device. Theprocessing device executes the instructions on the memory device and iscaused to receive a dataset and determine a plurality of data attributesthat represent the dataset. Each of the determined data attributes arerepresented by a percentage value, a proportion value of a whole valueor a count value. The processing device is further caused to associate adisplay-type with each determined attribute according to the value withwhich the determined data attribute is represented. For an example, apercentage display-type is associated with the percentage value, aproportion display-type is associated with the proportion value of thewhole value and a count display-type is associated with the count value.The percentage display-type indicates the percentage value with anexposed length of a first shape corresponding to the percentage value.The proportion display-type indicates the proportion value of the wholevalue as a wedge-shape having a size corresponding to the proportionvalue. The count display-type indicates the count value with a segmentedsecond shape, the number of segments in the segmented second shapecorrespond to the count value. The processing device is further causedto generate instructions for rendering a concentric visualization datastructure that includes a least one percentage display-type, at leastone proportion display-type and at least one count display-type. Inresponse to the instructions, the processing device is caused to render,on the display, the concentric visualization data structure as an imageof at least first, second and third concentric shapes which correspondto the percentage display-type, the proportion display-type and thecount display-type, respectively.

BRIEF DESCRIPTION OF THE DRAWINGS

Non-limiting and non-exhaustive examples are described with reference tothe following Figures.

FIG. 1 is an example configuration of an environment that is used forcreating and rendering concentric data visualization structures.

FIG. 2 is an example configuration of an application for creating andrendering concentric data visualization structures.

FIG. 3 is an example of data attributes to be calculated based ontransactional data.

FIG. 4A-1 and FIG. 4A-2 illustrate examples a of a percentage ring.

FIGS. 4B-4C illustrate examples of a proportion ring and a count ring,respectively.

FIG. 5 is an example of a single concentric data visualization structurerepresenting 26 data attributes.

FIG. 6 is an example of a plurality of different concentric datavisualization structures for a single dataset.

FIG. 7 is a flowchart illustrating a method for creating and renderingconcentric data visualization structures.

FIG. 8 is block diagram of an example computing device.

DETAILED DESCRIPTION

Various embodiments will be described in detail with reference to thedrawings that form a part hereof and, in which are shown by way ofillustrations, specific embodiments or examples. Embodiments can bepracticed as methods, systems or device. Accordingly, embodiments maytake the form of a hardware implementation, a software implementation,or an implementation combining both hardware and software. The followingdetailed description is therefore not to be taken in a limiting sense,and the scope of the present disclosure is defined by the appendedclaims and their equivalents.

As noted in the Summary, the present disclosure is directed to systemsand methods for creating and rendering concentric data visualizationstructures. The concentric data visualization structures have theability to represent virtually any number of features associated withsmall or large datasets. The data visualization structures are createdand rendered in the form of a concentric ring diagram (however, shapesother than a ring can be used), wherein a plurality of concentric ringsis used to represent a plurality of data attributes associated with adataset. In certain examples, the dataset represents spendingtransactions between a retail guest and a retailer. Further, in certainexamples, the spending transactions are those occurring at one or morephysical sites of the retailer and/or one or more e-retail websites ofthe retailer. The spending transactions are analyzed to determine one ormore data attributes; the determined data attributes are typicallyexpressed in the form of a numerical value. One of three ring-types isassigned to each data attribute according to the type of data attribute.The three ring-types include: a percentage ring, a proportion ring, anda count ring. Display features of the rings are defined to assist indistinguishing one ring from another. Such display features can include,but are not limited to, a concentric display order, a display color, adisplay pattern, and an inner and outer diameter of the ring (e.g.,thickness). The determined data attributes, assigned rings and displayfeatures are used to generate instructions for constructing one or moreof the concentric ring diagrams. The one or more concentric ringdiagrams are then rendered as one or more visual images on one or moredisplay devices according to the instructions providing a compactvisualization of a plurality of data attributes. In certain embodiments,26 data attributes are visualized in a single concentric ring diagramwhile in other embodiments the 26 data attributes are spread among aplurality of concentric ring diagrams. A number of data attributesgreater or lesser than 26 data attributes in a single concentric ringdiagram are also possible.

Referring to FIG. 1, an example configuration of an environment 100 forcreating and rendering concentric data visualization structures isillustrated. The environment 100 preferably includes one or more datagenerators to establish a dataset which can be utilized in the creationand rendering of concentric data visualization structures according tothe present in disclosure. In the example of FIG. 1, the data generatorscomprise retail guests 102, e.g. guests 102 a and 102 b, and a retailer103 with the generated data being representative of the spendingtransactions between the retail guests 102 and the retailer 103. In theexample of FIG. 1, the retailer 103 is represented by both physicalretail sites 104 and e-retail websites 106. Each physical retail site104, e.g., physical retail site 104 a and 104 b, utilizes one or moreretail computing devices 105, e.g., retail computing device 105 a, 105b, for generating, tracking, transmitting and/or receiving data relatedto guest/retailer spending transactions. Each e-retail website 106, e.g.e-retail website 106 a and 106 b, is accessed via one or more e-retailcomputing devices 107, e.g. e-retail computing device 107 a and 107 b,which can be used for generating, transmitting and/or receiving datarelated to guest/retailer spending transactions.

It should be noted that, while the present disclosure utilizes anexample of transactional data in the creation of concentric datavisualization structures, the data may comprise any type of numericaldata that can be analyzed to a proportion, a percentage or a count.

The data generated from the spending transactions between guests 102 andthe retailer 103 are transmitted through a network 108 and stored in oneor more databases 110 (e.g., database 110 a, database 110 b, database110 c). The data stored by the one or more databases 110 is accessiblevia network 108 (or direct access) by one or more server computingdevices 112 (e.g., server computing devices 112 a, server computingdevices 112 b, server computing devices 112 c). The one or more servercomputing devices 112 operate on the data to determine data attributesof the data as well as to create and render one or more concentric datavisualization structures, which are displayed on one or more datavisualization computing devices 114 (e.g., data visualization computingdevice 114 a, data visualization computing device 114 b, datavisualization computing device 1104 c). Note the environment 100 is butone possible configuration of an environment for creating and renderingconcentric data visualization structures and, as known by those skilledin the art, can be condensed or expanded to include a fewer or greaternumber of elements than that depicted. For example, all functions fortracking data, analyzing data, creating and rendering one or moreconcentric data visualization structures, and displaying the concentricdata visualization structures could be performed on a single computingdevice.

In a basic configuration, the one or more e-retail computing devices 107are personal or handheld computers having both input elements and outputelements operated by the one or more guests 102. For example, the one ormore e-retail computing devices 107 may include one or more of: a mobiletelephone; a smart phone; a tablet; a phablet; a smart watch; a wearablecomputer; a personal computer; a desktop computer; a laptop computer; agaming device/computer (e.g., Xbox); a television; and the like. Thislist is only and should not be considered as limiting. Any suitablee-retail computing device 107 for generating and/or tracking spendingtransactions between guests 102 and the retailer 103 can be used.Similarly the one or more retail computing devices 105 are computingdevices having both input and output elements operated by one or moreretail employees that are capable of generating and/or trackingtransactional spending data relating to in-store retail spendingtransactions occurring at the physical retail site 104.

The transactional spending data between guests 102 and the retailer 103generally includes how much is spent by a guest 102 at the one or morephysical retail sites or on the one or more e-retail websites 106 aswell as how many trips the guest 102 has made to the physical retailsite 104 or the e-retail website 106. More specific examples oftransactional spending data are detailed herein.

In certain embodiments, the network 108 is a computer network such as anenterprise intranet and/or the Internet. In this regard, the network 108may include a Local Area Network (LAN), a Wide Area Network (WAN), theInternet, wireless and wired transmission mediums. In certainembodiments, server computing devices 112 may communicate with somecomponents of the environment via a local network (e.g., an enterpriseintranet), whereas another server computing device 112 may communicatewith other components of the environment via a wide area network (e.g.,the Internet). In addition, the aspects and functionalities describedherein may operate over distributed systems (e.g., cloud-based computingsystems), where application functionality, memory, data storage andretrieval and various processing functions may be operated remotely fromeach other over a distributed computing network, such as the Internet oran intranet.

In a basic configuration, server computing devices 112 may include atleast a processing unit and a system memory for executingcomputer-readable instructions. In some aspects, server computingdevices 112 may comprise one or more server computing devices 112 in adistributed environment (e.g., cloud-based computing environment).Server computing devices 112 may provide data regarding transactions toand from e-retail computing devices 107 and/or data visualizationcomputing devices 114.

In a basic configuration, the data visualization computing devices 114are generally laptop or desktop computing devices capable of displayingconcentric data visualization structures. However, the datavisualization computing devices 114 may be any type of computing devicecapable of displaying the concentric data visualization structures(e.g., a mobile telephone; a smart phone; a tablet; a phablet; a smartwatch; a wearable computer; a personal computer; a gamingdevice/computer (e.g., Xbox); a television; and the like. In certainconfigurations, the data visualization computing devices 114 arereplaced with monitors for viewing the concentric data visualizationstructures.

In certain embodiments, the server computing devices 112 executeinstructions of a concentric data visualization structure application.Referring to FIG. 2, an example configuration of a concentric datavisualization structure application 200 is illustrated. As shown theconcentric data visualization structure application includes a dataintake module 202, a data analysis module 204, a ring-type assignmentmodule 206, a feature assignment module 208, a visualization instructionmodule 210, and a rendering module 212.

The data intake module 202 receives transactional data (e.g., thetransactional data stored on server computing devices 112) for aspecific cluster or grouping of guests 102 that have purchased itemsfrom one or more physical retail sites 104 and/or from one or moree-retail websites 106 of the retailer 103. By way of example, a physicalretail site of the retailer TARGET® may comprise a TARGET® store whilean e-retail website of the retailer TARGET® may comprise TARGET.com. Asindicated, the transactional data can be associated with a specificcluster of guests 102 according to a cluster definition. For example, acluster definition may include guests 102 that have a specific zip codeor area code, guests 102 that spend at a specific physical retail site,guests 102 that spend over or under a certain amount, guests 102 thatare known to have an income above or below an amount, or guests 102 thatsome other common identifiable characteristic. In certain exampleembodiments, the transactional data can be associated with one or morespecific physical retail sites 104 and/or one or more specific e-retailwebsites 106 of the retailer 103 according to retailer definition. Forexample, a retailer definition may include only physical retail sites104 (worldwide, national, by state, by city, etc.) or may include onlye-retail websites (worldwide, by country, etc.) or a combination ofspecific physical retail sites 104 and specific e-retail websites 106.

The transactional data of the data intake module 202 is provided to thedata analysis module 204. The data analysis module 204 analyzes thetransactional data to provide analysis results according to a pluralityof data attributes having pre-defined data attribute definitions for thedetermination of a representative numerical value. In certain exampleembodiments, the plurality of data attributes comprises exactly 26 dataattributes. However, a greater or lesser number of data attributes canbe utilized as desired or as suitable to a specific dataset. Anabbreviated listing of the 26 data attributes is provided in the Tableof FIG. 3 while a more detailed listing of the 26 data attributes isprovided below and includes:

1. A determination of a percentage of guests with retail card spending(e.g. a retail credit or debit card associated with a retailer and/ore-retailer) at a specific one or more physical retail sites and/or oneor more associated e-retail websites.

2. A determination of a percentage of guests with spending only during apre-defined holiday season (e.g. from Thanksgiving in November to theNew Year) at the specific one or more physical retail sites and/or oneor more associated e-retail websites.

3. A determination of the average number of trips by spending guests tothe specific one or more physical retail sites and/or one or moreassociated e-retail websites in the last year.

4. A determination of the average number of trips by spending guests tothe specific one or more physical retail sites and/or one or moreassociated e-retail websites in a last predefined number of days (e.g.the last 84 days).

5. A determination of the average ratio of retail card spending to totalspending for the guests at the specific one or more physical retailsites and/or one or more associated e-retail websites in the last year.

6. A determination of the average total sales in the last year by theguests at the specific one or more physical retail sites and/or one ormore associated e-retail websites.

7. A determination of the average sales of grocery products at thespecific one or more physical retail sites by guests in the last year.

8. A determination of the average sales of essential beauty products atthe specific one or more physical retail sites by guests in the lastyear.

9. A determination of the average sales of apparel/accessory products atthe specific one or more physical retail sites by guests in the lastyear.

10. A determination of the average sales of hardline products at thespecific one or more physical retail sites by guests in the last year.

11. A determination of the average sales of home products at thespecific one or more physical retail sites by guests in the last year.

12. A determination of the average sales of grocery products via thee-retailer website by guests in the last year.

13. A determination of the average sales of essential beauty productsvia the e-retailer website by guests in the last year.

14. A determination of the average sales of apparel/accessory productsvia the e-retailer website by guests in the last year.

15. A determination of the average sales of hardline products via thee-retailer website by guests in the last year.

16. A determination of the average sales of home products via thee-retailer website by guests in the last year.

17. A determination of the average number of trips by the spendingguests to the specific one or more physical retail sites for thepurchase of grocery products in the last year.

18. A determination of the average number of trips by the spendingguests to the specific one or more physical retail sites for thepurchase of essential beauty products in the last year.

19. A determination of the average number of trips by the spendingguests to the specific one or more physical retail sites for thepurchase of apparel/accessory products in the last year.

20. A determination of the average number of trips by the spendingguests to the specific one or more physical retail sites for thepurchase of hardline products in the last year.

21. A determination of the average number of trips by the spendingguests to the specific one or more physical retail sites for thepurchase of home products in the last year.

22. A determination of the average number of trips by the spendingguests via the e-retailer website for the purchase of grocery productsin the last year.

23. A determination of the average number of trips by the spendingguests via the e-retailer website for the purchase of essential beautyproducts in the last year.

24. A determination of the average number of trips by the spendingguests via the e-retailer website for the purchase of apparel/accessoryproducts in the last year.

25. A determination of the average number of trips by the spendingguests via the e-retailer website for the purchase of hardline productsin the last year.

26. A determination of the average number of trips by the spendingguests via the e-retailer website for the purchase of home products inthe last year.

As indicated herein, the data analysis module 204 provides a result foreach data attribute that is in the form of a numerical value based on anumerical calculation/determination. The numerical value isrepresentative of the corresponding data attribute within thetransactional data provided for analysis.

The data attributes determined by the data analysis module 204 areprovided to the ring-type assignment module 206. The ring-typeassignment module 206 assigns one of three types of rings to each dataattribute. The three types of rings include a percentage ring, aproportion ring and a count ring.

The percentage ring visually represents a percentage and is indicated byan arc length. Referring to FIG. 4A-1, a first example of a percentagering 402 a is illustrated. Percentage ring 402 a represents a percentageof 100% and is illustrated by a complete circle. Referring to FIG. 4A-2,a second example of a percentage ring 402 b is illustrated. Percentagering 402 b represents a percentage of approximately 60% since the arclength is approximately 60% of a total circle. In the example of the 26data attributes, the percentage ring is used to represent dataattributes 1, 2 and 5.

The proportion ring visually represents percentages of a whole and isanalogous to a pie chart. FIG. 4B illustrates an example of a proportionring 404. Proportion ring 404 is divided into ten wedges, e.g. wedgesA-J, with the size of the wedge representative of the percentage of thewhole. For example, wedge A represents approximately 23% of the whole,wedge B represents approximately 20% of the whole, wedge C representsapproximately 12% of the whole, etc. Each wedge represents one dataattribute and, as such, with a proportion ring, a plurality of dataattributes is combined into a single ring. It is possible for one ormore of the wedges to have a value of 0% thereby eliminating the wedgefrom the proportion ring. A thickness X of the proportion ring canprovide additional information about another attribute.

In the example of the 26 data attributes, a first proportion ring isused to represent data attributes 7-16, with each data attributecomprising a corresponding wedge representing a percentage of the wholeof average sales for all products at the specific one or more physicalretail sites and/or the e-retailer website by guests in the last year. Athickness of the first proportion ring is proportional to attribute six(e.g. avg. total sales in last 365 days). A second proportion ring isused to represent data attributes 17-26, with each data attributecomprising a corresponding wedge representing a percentage of the wholeof average number of trips by the spending guests to the specific one ormore physical retail sites and/or the e-retailer website for thepurchase of all products in the last year. A thickness of the secondproportion ring is proportional to attribute three (e.g. avg. number oftrips in last 365 days).

The count ring visually represents a count via the number of segments inwhich the ring is divided. FIG. 4C illustrates an example of a countring wherein count ring 406 represents a count of 14 as the count ring406 include 14 segments 408. In the example of the 26 data attributes, acount ring can be used to represent data attributes 3 and 4.

The determinations of the data attributes made by the data analysismodule 204 and the identification of the ring-type assigned by thering-type assignment module 206 are provided to the feature assignmentmodule 208. The feature assignment module assigns features such as athickness (e.g. inner radius and outer radius) for each of the rings aswell as a color, pattern and/or any other characteristic that might bedesirable to differentiate one ring from another in display of aconcentric data visualization structure. In the instance of theproportion ring, each of the wedges is assigned a unique color ordisplay pattern to differentiate from the other wedges within the ring.

In certain example embodiments, the features of the rings are assignedto accommodate the display of all 26 data attributes in a single diagramof concentric circles using one or more of percentage rings, one or moreof proportion rings and one or more of count rings. In certain exampleembodiments, and for ease of reading, percentage rings are provided asthe outermost rings, segment rings are provided as the next outer mostrings and proportion rings comprise the innermost rings. However, aplurality of rings can be displayed in any desired order. In certainembodiments, less than all data attributes are represented in a singlediagram of a concentric data visualization structure. In certainembodiments, all three ring-types are represented in single diagramwhile in other embodiments less than all three ring-types arerepresented in a single diagram. In certain example embodiments, five ormore data attributes are represented in a single diagram. In certainexample embodiments, ten or more data attributes are represented in asingle diagram. In certain example embodiments, 15 or more dataattributes are represented in a single diagram. In certain exampleembodiments, 20 or more data attributes are represented in a singlediagram. In certain example embodiments, 26 or more data attributes arerepresented in a single diagram.

FIG. 5 illustrates an example of diagram 500 containing ringsrepresenting all 26 data attributes. The diagram 500 includes percentagering A representing data attribute one and percentage ring Brepresenting data attribute two. Further, the diagram 500 includes countring C representing data attribute three and count ring D representingdata attribute four. Attributes 7-16 are represented on the diagram 500by proportion ring E. Attribute five is represented on the diagram 500as percentage ring F. Finally, the diagram 500 includes proportion ringG representing data attributes 17-26. Proportion rings E and G providefurther data insight based on their thickness. For example, thethickness of proportion ring E is proportional to attribute six (e.g.avg. total sales in last 365 days) and the thickness of proportion ringG is proportional to attribute three (e.g., avg. number of trips in last365 days).

In certain example embodiments, the feature assignment module 208 canadditionally be utilized to define features in the form of the contentto be provided in a displayed explanation of each ring. For example, thecontent may include a name, definition and/or examplecalculation/determination for one or more data attributes, a name,definition and/or example calculation for one or more of the rings, thecontent may include a name, definition and/or examplecalculation/determination for each wedge of a proportional ring, etc.Other desirable and/or appropriate content can also be included. Thecontent can be displayed, for example, in legend proximate the diagramor in hover notes displayed as a user moves a cursor over a ring and/orwedge of the diagram. Other content displays are also possible.

Data regarding assigned ring-types and features of the rings in relationto the data attributes which are to be represented in a diagram of aconcentric data visualization structure are provided to thevisualization instruction module 210. The visualization instructionmodule 210 generates the instructions needed create a visualrepresentation of the rings of a diagram based on the providedinformation (e.g., attribute, ring-type, features). In certain exampleembodiments, the visualization instruction module 210 comprises anapplication entitled Bokeh. Bokeh is an interactive visualizationlibrary for Python that enables meaningful presentation of very large orstreaming datasets in modern web browsers. In certain exampleembodiments, the “annular wedge” function of Bokeh is used to generatethe rings of the diagram. Other applications for the visualization ofcomplex and/or large sets data may also, or alternatively, be used togenerate the concentric rings of the diagram. Such other applicationscan include, but are not limited to, D3.js, RAWGraphs, Tableau,Matplotlib, Plotly, NVD3, Google Charts, and Desmos.

The instructions generated by the visualization instruction module 210to produce the visual image of the concentric data visualizationstructure are provided to the rendering module 212. The rendering module212 renders the concentric data visualization structure as an image on adisplay device according to the instructions provided by thevisualization instruction module 210. In certain example embodiments,the rendering module comprises a rendering instruction in the Bokehapplication described above. In certain example embodiments, therendering module is an element of a drawing application or tool while inother embodiments the rendering module is a stand-alone applicationspecifically dedicated to rendering of images. In certain exampleembodiments, the rendering occurs in a business tool application (or therendered image is provided to the business tool application) that isused to determine patterns, trends, correlations, etc. in a businessrelated data.

FIG. 6 illustrates one example of a plurality of ring diagrams renderedby the rendering module 212. Each of the ring diagrams represents all 26data attributes (note that certain attributes may be at a zero or nearzero value and are therefore not provided on the ring diagram) as wellas the ring types assigned to the data attributes and the featuresassigned to the rings. Note that the right-most, upper-most diagramcorresponds to the diagram 500 of FIG. 5. Each of the ring diagrams ofFIG. 6 are presented in the same ring order as FIG. 5. However, as notedearlier, any desired ring order can be used. Examples of various hovernotes displayed as a user moves a cursor over a ring and/or a wedge ofthe diagram are also illustrated in FIG. 6. Each hover note provides atext description of the relevant attribute of the ring over which thecursor is moving or resting, and also provides a numerical value of therelevant attribute. For example, hover note 602 is an example of thetext description and numerical value that is displayed when moving acursor over wedge A of proportion ring 601. Hover note 604 is an exampleof the text description and numerical value that is displayed whenmoving a cursor over the count ring 603. Hover note 606 is an example ofthe text description and numerical value that is displayed when moving acursor over a middle 605 of a diagram, notably the value of the averagetotal sales in the last 365 days (e.g., attribute six) is presented.Hover note 608 is an example of the text description and numerical valuethat is displayed when moving a cursor over the percentage ring 607.

FIG. 7 is a flowchart illustrating a method 700 for creating andrendering a concentric data visualization structures. As shown, themethod 700 begins with receiving data (S702) regarding a specificcluster of guests and their transactions (e.g. spending transactions)with a retailer at one or more physical sites of the retailer and/or oneor more e-retail websites of the retailer. The transaction data is thenanalyzed (S704) to determine various data attributes that exist withinthe data. The data attributes determined under analysis are generallypre-defined data attributes that provide insight into the transactiondata. In certain example embodiments, the pre-defined data attributescomprise the 26 data attributes described here and illustrated in thetable of FIG. 3. A greater or fewer number of data attributes may beused as appropriate to the dataset or as desired.

Each of the determined data attributes, which typically comprisenumerical values (however, representation of a data attribute in a formother than a numerical value is also possible), is then assigned one ofthree ring-types (S706), e.g., a percentage ring, a proportion ring orcount ring, that is suited to the specific determined data attribute.The features of each of the assigned rings are then defined (S708) withvarious display features, e.g. thickness of the ring, color or patternof the ring, color or pattern of wedges within the ring, concentricdisplay order of the rings, etc. The values of the determined dataattributes, the assigned rings and their defined features are then usedto generate one or more instructions for rendering an image (e.g. adiagram of a concentric data visualization structure), representing thedata attributes, rings and features (S710). In certain exampleembodiments all determine data attributes are included in the ringdiagram while in other example embodiments fewer than all determinedattributes are included in the ring diagram. In certain exampleembodiments, the number of determined data attributes to be used in aring diagram are manually selected by a user while in other exampleembodiments one or more pre-defined selection formulas are used inautomatically selecting the defined data attributes to be used in one ormore specific ring diagrams. The one or more ring diagram imagesspecified by the instructions for constructing the image (or images) arethen rendered to produce one or more visual images on one or moredisplay devices (S712).

The method described above includes steps occurring in a specificsequence. However, it should be noted that the steps of the method canbe performed in any suitable sequence and can include a greater orlesser number of steps than those provided in FIG. 7. Further, therecited steps can additionally, or alternatively, be combined or dividedto reduce or increase the number of steps, respectively.

Referring now to FIG. 8, an example block diagram of a computing device800 is shown that is useable to implement aspects of the environment 100of FIG. 1 for creating and rendering concentric data visualizationstructures. In the embodiment shown, the computing device 800 includesat least one central processing unit (“CPU”) 812, a system memory 820,and a system bus 818 that couples the system memory 820 to the CPU 812.The system memory 820 includes a random access memory (“RAM”) 822 and aread-only memory (“ROM”) 824. A basic input/output system that containsthe basic routines that help to transfer information between elementswithin the computing device 800, such as during startup, is stored inthe ROM 824. The computing device 800 further includes a mass storagedevice 826. The mass storage device 826 is able to store softwareinstructions and data.

The mass storage device 826 is connected to the CPU 812 through a massstorage controller (not shown) connected to the system bus 818. The massstorage device 826 and its associated computer-readable storage mediaprovide non-volatile, non-transitory data storage for the computingdevice 800. Although the description of computer-readable storage mediacontained herein refers to a mass storage device, such as a hard disk orsolid state disk, it should be appreciated by those skilled in the artthat computer-readable data storage media can include any availabletangible, physical device or article of manufacture from which the CPU812 can read data and/or instructions. In certain embodiments, thecomputer-readable storage media comprises entirely non-transitory media.

Computer-readable storage media include volatile and non-volatile,removable and non-removable media implemented in any method ortechnology for storage of information such as computer-readable softwareinstructions, data structures, program modules, or other data. Exampletypes of computer-readable data storage media include, but are notlimited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid statememory technology, CD-ROMs, digital versatile discs (“DVDs”), otheroptical storage media, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other medium which canbe used to store the desired information and which can be accessed bythe computing device 800.

According to various embodiments of the invention, the computing device800 may operate in a networked environment using logical connections toremote network devices through a network 810, such as a wirelessnetwork, the Internet, or another type of network. The computing device800 may connect to the network 110 through a network interface unit 814connected to the system bus 818. It should be appreciated that thenetwork interface unit 814 may also be utilized to connect to othertypes of networks and remote computing systems. The computing device 800also includes an input/output unit 816 for receiving and processinginput from a number of other devices, including a touch user interfacedisplay screen, or another type of input device. Similarly, theinput/output unit 816 may provide output to a touch user interfacedisplay screen or other type of output device.

As mentioned briefly above, the mass storage device 826 and the RAM 822of the computing device 800 can store software instructions and data.The software instructions include an operating system 830 suitable forcontrolling the operation of the computing device 800. The mass storagedevice 826 and/or the RAM 822 also store software instructions, thatwhen executed by the CPU 812, cause the computing device 800 to providethe functionality discussed in this document. For example, the massstorage device 826 and/or the RAM 822 can store software instructionsthat, when executed by the CPU 812, cause the computing device 800 toreceive and analyze data as well as create and render concentricvisualization data structures.

As should be appreciated, the various aspects (e.g., portions,components, etc.) described with respect to the figures herein are notintended to limit the systems and methods to the particular aspectsdescribed. Accordingly, additional configurations can be used topractice the methods and systems herein and/or some aspects describedcan be excluded without departing from the methods and systems disclosedherein.

Similarly, where steps of a process/method are disclosed, those stepsare described for purposes of illustrating the present methods andsystems and are not intended to limit the disclosure to a particularsequence of steps. For example, the steps can be performed in differingorder, two or more steps can be performed concurrently, additional stepscan be performed, and disclosed steps can be excluded without departingfrom the present disclosure.

Although specific aspects are described herein, the scope of thetechnology is not limited to those specific aspects. One skilled in theart will recognize other aspects or improvements that are within thescope of the present technology. Therefore, the specific structure,acts, or media are disclosed only as illustrative aspects. The scope ofthe technology is defined by the following claims and any equivalentstherein.

What is claimed:
 1. A method for visualizing data: receiving a dataset;determining a plurality of data attributes that represent the dataset,wherein each of the determined data attributes are represented by apercentage value, a proportion value of a whole value or a count value;associating a ring-type with each determined attribute according to thevalue with which the determined data attribute is represented, wherein apercentage ring-type is associated with the percentage value, aproportion ring-type is associated with the proportion value of thewhole value, and a count ring-type is associated with the count value,wherein the percentage ring-type indicates the percentage value with anexposed arc length corresponding to the percentage value, wherein theproportion ring-type indicates the proportion of the whole value with awedge-shape having a size corresponding to the proportion value, andwherein the count ring-type indicates the count value with a segmentedring, the number of segments in the ring corresponding to the countvalue; and generating instructions for rendering a concentricvisualization data structure that includes a least one percentagering-type, at least one proportion ring-type and at least one countring-type; and based on the instructions, rendering the concentricvisualization data structure as an image of at least first, second andthird concentric rings which correspond to the percentage ring-type, theproportion ring-type and the count ring-type, respectively, and whereinthe image of each of the at least first, second and third concentricrings is independent of the image of the other two concentric rings. 2.The method of claim 1, further comprising defining display features ofeach of the ring types.
 3. The method of claim 2, wherein the displayfeatures a display color, a display pattern, a concentric ring order, ora ring thickness.
 4. The method of claim 3, wherein the concentric ringorder includes the percentage ring-type as an outermost ring of thefirst, second and third concentric rings in the image.
 5. The method ofclaim 4, wherein the concentric ring order includes the count-ring typeas intermediate ring of the first, second and third concentric rings inthe image and wherein the concentric ring order includes the proportionring-type as the innermost of first, second and third concentric ringsin the image.
 6. The method of claim 1, further comprising assigning theproportion ring-type to a plurality of the determined attributes,wherein the plurality of determined attributes is combined to representthe whole.
 7. The method of claim 1, wherein the rendered image includesa first plurality of concentric rings each of which corresponds to apercentage ring-type.
 8. The method of claim 7, wherein the renderedimage includes a second plurality of concentric rings each of whichcorresponds to a proportion ring-type.
 9. The method of claim 8, whereinthe rendered image includes a third plurality of concentric rings eachof which corresponds to a count ring-type.
 10. The method of claim 1,further comprising displaying hover-activatable content for eachrespective ring, the hover-activatable content describing the determinedattribute associated with the displayed ring.
 11. The method of claim 1,wherein the rendered image represents at least 20 different determinedattributes.
 12. The method of claim 1, wherein the rendered imagerepresents at least 26 different determined attributes.
 13. The methodof claim 1, wherein the dataset includes transactional spending datacorresponding to transactions between a retail guest and a retailer. 14.The method of claim 13, wherein the transactions corresponding to aphysical site retailer, a web-site retailer, or a combined physical siteand web-site retailer.
 15. A concentric data visualization structure fordisplaying a plurality of attributes specific to a dataset, theconcentric data visualization structure comprising: an image of apercentage ring indicating a percentage representative of an attributeof the dataset, wherein the percentage ring comprises an arc having anarc length corresponding to the percentage; an image of a proportionring including a plurality of wedges, wherein each wedge represents apercentage proportion of a whole, wherein each proportion isrepresentative of an attribute of the dataset, and wherein whendisplayed the plurality of wedges entirely fill the proportion ring; andan image of a count ring indicating a count value representative of anattribute of the dataset, wherein the count ring comprises a segmentedcircle wherein a number of the segments of the circle correspond to thecount value, wherein the images of each of the percentage ring, theproportion ring and the count ring within the concentric datavisualization structure are independent of the other two rings.
 16. Theconcentric data visualization structure of claim 15, further comprisinga plurality of percentage rings, wherein each of the plurality ofpercentage rings represents a different attribute of the dataset. 17.The concentric data visualization structure of claim 16, furthercomprising a plurality of proportion rings, wherein each of theplurality of proportion rings represents a different whole of thedataset.
 18. The concentric data visualization structure of claim 17,further comprising a plurality of count rings, wherein each of theplurality of count rings represents a different attribute of thedataset.
 19. The concentric data visualization structure of claim 18,wherein the plurality of percentage rings comprises the outermost ringsof the data visualization structure, the plurality of count ringscomprises the intermediate rings of the data visualization structure andwherein the plurality of percentage rings comprises the innermost ringsof the data visualization structure.
 20. A system for visualizing dataof a dataset, comprising: a display device; a memory device storingexecutable instructions; a processing device in communication with thedisplay device and the memory device, wherein the processing deviceexecutes the instructions on the memory device and is caused to: receivea dataset; determine a plurality of data attributes that represent thedataset, wherein each of the determined data attributes are representedby a percentage value, a proportion value of a whole value or a countvalue; associate a display-type with each determined attribute accordingto the value with which the determined data attribute is represented,wherein a percentage display-type is associated with the percentagevalue, a proportion display-type is associated with the proportion valueof the whole value, and a count display-type is associated with thecount value, wherein the percentage display-type indicates thepercentage value with an exposed length of a first shape correspondingto the percentage value, wherein the proportion display-type indicatesthe proportion value of the whole value as a wedge-shape having a sizecorresponding to the proportion value, and wherein the countdisplay-type indicates the count value with a segmented second shape,the number of segments in the segmented second shape corresponding tothe count value; and generate instructions for rendering a concentricvisualization data structure that includes a least one percentagedisplay-type, at least one proportion display-type and at least onecount display-type; and based on the instructions, render, on thedisplay device, the concentric visualization data structure as an imageof at least first, second and third concentric shapes which correspondto the percentage display-type, the proportion display-type and thecount display-type, respectively, and wherein the image of each of theat least first, second and third concentric shapes is independent of theimage of the other two concentric shapes.